A Warrant That Pays Out Only If Marvell Delivers

On August 19, 2026, Marvell Technology issued Alphabet's Google a warrant to buy up to 58.97 million Marvell shares at $206.58 each, exercisable until August 18, 2033. At full exercise, that is roughly $12.2 billion - about 11.3 billion euros, or 9.6 billion pounds - Google would pay Marvell if it chose to buy every share. That distinction matters: the $12.2 billion is what Google would spend to exercise the option, not money Marvell is paying out or a chip order Google has committed to.

The structure is what makes this different from an ordinary strategic investment. Roughly 1.36 million shares vest automatically in equal quarterly installments over the first year. The remaining 57.6 million vest only as Marvell actually books qualifying revenue from Google's purchases, in tranches of about 240,000 shares for every $500 million billed, running from Marvell's third fiscal quarter of 2027 through the end of fiscal 2033. Full vesting would require $120 billion in cumulative Google orders over that period - a ceiling on the incentive, not a forecast of what will happen.

Two Suppliers, Two Different Jobs Inside the Same Chip Stack

Marvell is not taking over Google's Tensor Processing Unit design. Broadcom still holds that role: the two companies signed their own long-term agreement in April 2026 covering future TPU generations and AI-rack components through 2031, and Broadcom remains, in its own words, deeply entrenched in Google's AI silicon roadmap. What Marvell picks up instead is the silicon built around the TPU - AI inference accelerators, networking chips, storage controllers, memory interface controllers and near-memory computing technology that let a TPU cluster actually move and process data at scale.

That division of labor is the point. Google is not swapping vendors; it is adding a second, financially incentivized one inside the same ecosystem, for the components that sit next to - not inside - its flagship AI chip. It is a narrower slice of the stack, but a slice large enough that Marvell's own investors treated it as a genuine expansion of the company's cloud-AI business.

Why Broadcom's Stock Fell on Someone Else's Deal

The market did not read this as a footnote. Marvell shares rose more than 6.6 percent the day the deal was disclosed, closing near $230, while Broadcom fell more than 5.5 percent to roughly $359. Alphabet's own stock barely moved. Analysts covering the announcement were explicit about why: Marvell is not displacing Broadcom's core TPU role, but it is now positioned to capture a growing share of Google's future AI-silicon spending in the categories around that chip - spending that would otherwise have gone entirely to Broadcom or been built in-house.

Marvell reports its fiscal second-quarter earnings on August 27, 2026, which will be the first chance for investors to press management on how much near-term revenue the Google relationship is actually expected to generate, beyond the long-dated vesting math in the warrant itself.

An Infrastructure Race Behind a Model Race Google Is Not Winning

The timing lines up with a wider pattern in how Google is competing. Prediction markets tracking which company will field the best AI model by the end of 2026 give Google only about a 7 percent chance, against roughly 66 percent for Anthropic, 14.5 percent for xAI and 8 percent for OpenAI. Google is not the favorite on model quality right now, by that measure, and it knows it.

What Google can still control is the cost, speed and specialization of the compute those models run on. Locking in a second, incentive-aligned silicon supplier - one that only gets paid in equity as it proves it can deliver - is a bet on infrastructure economics doing work that model benchmarks currently are not. It is a hedge against losing the AI race on two fronts instead of one.

What Dual-Sourced Silicon Means for Buyers Outside the US

None of this is US-only. Any organization running production AI workloads on Google Cloud's TPU infrastructure - a growing number of EU and UK enterprises using Vertex AI or dedicated TPU pods for training and inference - is exposed to how much chip capacity Google can secure, at what price, and from how many independent sources. A hyperscaler dependent on a single silicon vendor is a hyperscaler whose customers inherit that vendor's capacity constraints and pricing power during a shortage.

A second embedded supplier does not eliminate that risk, but it meaningfully reduces it, and it mirrors the logic EU policymakers have been pushing on cloud and chip vendors for their own sovereignty reasons: concentration in one supplier is a structural weakness, not just a procurement inconvenience. Watching whether Marvell's Google-linked revenue actually shows up in its upcoming earnings calls is now a genuine capacity-planning signal for anyone budgeting AI compute costs into 2027 and beyond.